Remote radio unit (rru) configuration controller

ABSTRACT

This disclosure describes techniques that enable a Remote Radio Unit (RRU) configuration controller to detect a misconfigured RRU on a base station node. The RRU configuration controller may be configured to capture telemetry data within a service sector of a base-station node. The RRU configuration controller may further determine a signal Quality of Service (QoS) associated with the service sector, based on the telemetry data. In doing so, the RRU configuration controller may determine whether the RRU associated with the service sector is misconfigured.

BACKGROUND

Mobile equipment networks provide real-time and continuous wirelesscommunication services to subscribers through the deployment of wirelessbase station nodes and related control and support infrastructure,collectively termed a radio access network (RAN). Typically, basestation nodes are deployed in a geometric arrangement to facilitatewireless service at any point within a geographic coverage area. Themost common geometric arrangement for a RAN deployment is a set ofhexagonal cells mapped over a geographic coverage area. Each cell has aradio tower constructed at the center.

Each base station node may include several Remote Radio Units (RRUs)that each service a radial sector of the geographic coverage area. Forexample, a base station node may include three RRUs that each service a120-degree radial sector of the geographic coverage area. Each RRU isconnected to a baseband unit using a dedicated cable. During maintenanceof such a base station node, field workers may inadvertently connect adedicated cable intended for one RRU with that of another RRU. The swapin cable connectivity at the RRU may cause a deterioration in a Qualityof Service (QoS) within the service sector, ultimately impactingsubscriber quality of experience. Present-day, field workers are taskedwith manually identifying and rectifying misconfigured RRUs.

The detailed description is set forth with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items or features.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is set forth with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items or features.

FIGS. 1A and 1B illustrate an example computing environment thatfacilitates the operation of the RRU configuration controller, inaccordance with at least one embodiment. FIG. 1A illustrates thecomputing environment within which the RRU configuration controllerinteracts with a base station node. FIG. 1B illustrates a detailed viewof a telemetry bin within the computing environment.

FIG. 2 illustrates a block diagram for an operation of the RRUconfiguration controller.

FIG. 3 illustrates various components of an example RRU configurationcontroller.

FIG. 4 illustrates an exemplary process for capturing telemetry datawithin a service sector of an RRU and determining whether the RRU ismisconfigured, in accordance with at least one embodiment.

FIG. 5 illustrates an exemplary process for determining whether an RRUis misconfigured or subject to a localized RF signal obstruction, inaccordance with at least one embodiment.

DETAILED DESCRIPTION

This disclosure describes techniques for detecting a misconfiguredRemote Radio Unit (RRU) at a base station node. Base station nodestypically include several RRUs that each serve a service sector of thebase station node's service area. An RRU configuration controller isdescribed that can dynamically infer the presence of a misconfiguredRRU. The RRU configuration controller may monitor user devices within aservice area of a base station node, capture corresponding telemetrydata, and infer whether an RRU serving the user devices is misconfiguredbased on an analysis of the telemetry data. Telemetry data may includedownlink throughput, uplink throughput, packet loss, latency, jitter,echo, or any suitable combination thereof.

Present-day, field workers are required to manually inspect and identifymisconfigured RRUs, which can lead to delays in detecting and correctinga misconfiguration. A misconfigured RRU may refer to an RRU that isconnected to a baseband unit using a cable intended for another RRU. Forexample, a first RRU may be connected to the baseband unit using asecond cable intended for a second RRU. The inadvertent cable swap maycause the RRU to experience a marked reduction in performance,ultimately impacting a subscriber's quality of experience.

The RRU configuration controller may be configured to capture andanalyze telemetry data of user devices within a service sector of a basestation node in real-time, or near-real-time, thus obviating a relianceon field workers to manually identify misconfigured RRUs. In turn, thetime taken to discover a misconfigured RRU is reduced, improving asubscriber's quality of experience. The term “real-time” is intended todescribe the instantaneous analysis of telemetry data relative to theactual time that the telemetry data is captured. “Near-real-time” refersto a temporal delay between the time that the telemetry data is capturedand the time that the telemetry data is analyzed. The temporal delay maybe one second, one minute, one hour, or any other suitably appropriatetime interval.

The RRU configuration controller may capture telemetry data of userdevices at a plurality of “telemetry bins” within a service sector.Telemetry bins may represent discrete geographic locations within aservice sector of a base station node from which an RF configurationcontroller may capture telemetry data associated with user devices. Forexample, if a user device transmits an RF signal (e.g. inbound oroutbound RF transmission) and moves into a geographic location that isproximate to a telemetry bin, the RRU configuration controller may pullthe telemetry data associated with the user device. Telemetry bins maybe software-based or hardware-based, or a suitable combination of both.For software-based telemetry bins, the RRU configuration controller maypull telemetry data from user devices that transmit RF signals and movewithin a predetermined proximity of the telemetry bin. Software-basedtelemetry bins rely on detecting RF signal transmissions from userdevices that are proximate to the telemetry bin at a time oftransmission. Hardware-based telemetry bins, such as beacons, employsuitable wireless communication protocols to detect the presence of auser device within a predetermined proximity of the telemetry bin. Oncedetected, the RRU configuration controller may pull the telemetry datafrom the user device.

Collectively, telemetry bins within a service sector may capture arepresentative portion of telemetry data transmitted within the servicesector. Thus, the telemetry data captured at telemetry bins within aservice sector may be associated with the RRU that is serving theservice sector.

To analyze the telemetry data in each service sector, the RRUconfiguration controller may overlay a polygon representation onto a mapof a service sector. The polygon representation may have a vertex at thebase station node and may overlay the substantial QoS bounds of theservice sector. Substantial QoS bounds of the service sector may bebased on the geographic area of the service sector within which theserving RRU can maintain RF signals within a signal QoS data that isgreater than or equal to a predetermined QoS threshold.

Therefore, the telemetry data gleaned from telemetry bins within thebounds of the polygon representation of a service sector areattributable to that service sector. The RRU configuration controllermay employ one or more trained-machine learning algorithms to analyzethe telemetry data and determine a signal QoS data for the servicesector. The signal QoS data may describe or measure the overallperformance of an RF signal associated with the RRU, based on thetelemetry data, and as experienced by the user device. To quantitativelymeasure signal QoS data, the RRU configuration controller may analyzesuitable combinations of the telemetry data, such as packet loss, bitrate, throughput, latency, availability, and jitter. The signal QoS datamay include measurements of a Reference Signal Received Power (RSRP)and/or Reference Signal Received Quality (RSRQ).

Performance of an RRU may be inferred by comparing a signal QoS data ofa service sector relative to a QoS threshold. The QoS threshold may bedefined by expected performance measures of the RRU. If the signal QoSdata is equal to the QoS threshold, the RRU is performing as expected.If the signal QoS data is greater than the QoS threshold, the RRU isperforming better than expected, and if the signal QoS data is less thanthe QoS threshold, the RRU is underperforming.

In some examples, the RRU configuration controller may determine the QoSthreshold based on historical telemetry data associated with the RRU.For example, the RRU configuration controller may retrieve, from a datastore, historical telemetry data associated with an RRU. The RRUconfiguration controller may employ one or more trained machine-learningalgorithms to analyze the historical telemetry data to determine a QoSthreshold. The QoS threshold may be based on any suitable combination ofsignal QoS data (e.g. downlink throughput, uplink throughput, packetloss, latency, jitter, or echo) or measurements thereof (e.g. RSRP orRSRQ).

The RRU configuration controller may generate a QoS score that reflectsan analysis of the signal QoS data relative to the QoS threshold. In oneembodiment, the QoS score may be based on the signal QoS data ofindividual telemetry bins. The RRU configuration controller mayaggregate the QoS scores of each telemetry bin to determine a QoS scorefor a service sector. In another embodiment, rather than calculating QoSscores for individual telemetry bins and then aggregating the QoSscores, the QoS score may be based on an aggregate signal QoS data forthe service sector.

The RRU configuration controller may also employ one or more trainedmachine-learning algorithms to analyze the telemetry data to determinechanges in signal QoS data across the geographic area of a servicesector. In this way, the RRU configuration controller may determinewhether an underperformance in signal QoS data is likely due to amisconfigured RRU. For example, if the signal QoS data at a specifictelemetry bin (e.g. discrete geographic position) reflectsunderperformance, while other signal QoS data (e.g. other telemetrybins) within the remaining regions of the service sector reflectsadequate performance, the RRU configuration controller may infer thatthe localized underperformance is inconsistent with a misconfigured RRU,and is more likely attributable to a physical or electromagnetic RFsignal obstruction. However, if the signal QoS data measured acrosstelemetry bins within a service sector reflects a uniformunderperformance or a uniform rate of signal attenuation that isrelative to distance from the base station node, the RRU configurationcontroller may infer that such underperformance may be attributable to amisconfigured RRU. RF signals typically degrade (e.g. signalattenuation) with distance from a transmitting source, which in thiscase is the RRU. Therefore, a uniform rate of signal attenuation withdistance from the RRU can reflect a properly configured RRU.

Accordingly, an analysis of the changes in signal QoS data may providethe RRU configuration controller with the ability to avoidfalse-positive declarations of a misconfigured RRU.

In response to determining that an RRU is misconfigured, the RRUconfiguration controller may generate a message for delivery to anoperator device associated with the base station node. The message mayindicate that the RRU is likely misconfigured. The operator device maybe associated with a field worker responsible for the base station node,an operator of the base station node, or any other suitable personnelthat may correct a misconfigured RRU.

Moreover, in response to determining that the RRU is misconfigured, theRRU configuration controller may infer that at least one other RRU isalso misconfigured because the misconfiguration is based on aninadvertent swap of cables from a common, baseband unit. Accordingly,the RRU configuration controller may analyze the service sectors of theremaining RRUs to identify at least one other RRU that is misconfigured.

Further, the term “techniques,” as used herein, may refer to system(s),method(s), computer-readable instruction(s), module(s), algorithms,hardware logic, and/or operation(s) as permitted by the contextdescribed above and through the document.

FIGS. 1A and 1B illustrate an example computing environment thatfacilitates the operation of the RRU configuration controller, inaccordance with at least one embodiment. FIG. 1A illustrates thecomputing environment within which the RRU configuration controllerinteracts with a tri-sector base station node. FIG. 1B illustrates adetailed view of a telemetry bin within a service sector of the basestation node. A tri-sector base station node refers to a base stationnode that has been divided into three service sectors. While FIGS. 1Aand 1B illustrate a tri-sector base station node, one of ordinary skillin part may appreciate that variations and modification can be made suchthat the RRU configuration controller 102 may operate to analyze a basestation node with any suitable plurality of sectors.

Referring to FIG. 1A, the RRU configuration controller 102 may capturetelemetry data 104 from a base station node 106 of a telecommunicationsnetwork 108, via one or more network(s) 110. The telecommunicationsnetwork 108 may provide telecommunications and data communications inaccordance with one or more technical standards, such as Enhanced DataRates for GSM Evolution (EDGE), Wideband Code Division Multiple Access(W-CDMA), High-Speed Packet Access (HSPA), Long Term Evolution (LTE), 5GNew Radio (5G NR), CDMA-2000 (Code Division Multiple Access 2000),and/or so forth. The telecommunications network 108 may include a corenetwork that may provide telecommunication and data services to multiplecomputing devices, such as user device(s) 112(1)-112(N).

The base station node 106 is traditionally responsible for handlingvoice and data traffic between user equipment and a telecommunicationsnetwork 108. The base station node 106 may be sectorized, meaning thatthe 360-degree service area planform is divided into several servicesectors. In the illustrated example, the base station node 106 isdivided into three service sectors, namely service sectors114(1)-114(3).

Each of the service sectors 114(1)-114(3) may be supported by dedicatedRRUs 116(1)-116(3). In the illustrated example, the RRU configurationcontroller 102 may overlay polygon representations 118(1)-118(3) over amap of the service sectors 114(1)-114(3) to reflect the geographic areawithin which the RRUs 116(1)-116(3) are expected to service.

Within each of the polygon representations 118(1)-118(3), the RRUconfiguration controller 102 may capture telemetry data 104 fromtelemetry bin(s) 120(1)-120(P). Each telemetry bin(s) 120(1)-120(P) mayrepresent geographic locations at which the RRU configuration controller102 capture telemetry data 104 from user devices 112(1)-112(N). Forexample, if one of the user device(s) 112(1)-112(N) transmits an RFsignal and moves into a geographic location that is proximate to atelemetry bin 120(1), the RRU configuration controller 102 may capturetelemetry data 104 associated with one of the user device(s)112(1)-112(N).

The RRU configuration controller 102 may analyze the telemetry data 104to determine a signal Quality of Service (QoS) data for each of theservice sectors 114(1)-114(3) of the base station node 106. The signalQoS data may measure the overall performance of RF signal transmissionswithin the serving sector, based at least in part on the telemetry data104. In one embodiment, the RRU configuration controller 102 mayaggregate the telemetry data 104 across telemetry bin(s) 120(1)-120(P)within a service sector 114(1) and determine the signal QoS data for theservice sector using the aggregated telemetry data. In anotherembodiment, the RRU configuration controller 102 may determine thesignal QoS data for each of the telemetry bin(s) 120(1)-120(P) within aservice sector, and determine the signal QoS data for the service sectorby aggregating the signal QoS data of each of the telemetry bin(s)120(1)-120(P).

The RRU configuration controller 102 may infer whether an RRU 116(1) ismisconfigured based on a comparison of signal QoS data for the servicesector and a predetermined QoS threshold.

In response to determining that the RRU 116(1) is misconfigured, the RRUconfiguration controller 102 may generate a message 122 for delivery toan operator device 124, via one or more network(s) 110. The message mayindicate that the RRU 116(1) is likely misconfigured. The message 122may further indicate that at least one other RRU, namely RRU 116(2) orRRU 116(3), is likely misconfigured since the misconfiguration ispremised on a cable swap from a common, baseband unit 126.

The RRU configuration controller 102 may operate on one or moredistributed computing resource(s). The one or more distributed computingresource(s) may include one or more computing device(s) that operate ina cluster or other configuration to share resources, balance load,increase performance, provide fail-over support or redundancy, or forother purposes. The one or more computing device(s) may include one ormore interfaces to enable communications with other networked devices,such as the operator device 124 and the user device 112(1)-112(N) viaone or more network(s) 110.

The one or more network(s) 110 may include public networks such as theInternet, private networks such as an institutional and/or personalintranet, or some combination of a private and public network(s). Theone or more network(s) can also include any type of wired and/orwireless network, including but not limited to local area network(LANs), wide area network(s) (WANs), satellite networks, cable networks,Wi-Fi® networks, Wi-Max networks, mobile communications networks (i.e.5G-NR, LTE, 3G, 2G), or any combination thereof.

Moreover, the operator device 124 and the user device 112(1)-112(N) mayinclude any sort of electronic device, such as a television unit, amultimedia streaming device, a cellular phone, a smartphone, a tabletcomputer, an electronic reader, a media player, a gaming device, apersonal computer (PC), a laptop computer, etc. The operator device 124and the user device 112(1)-112(N) may also include network devices thatact as intermediaries with the Internet. It is noteworthy that theInternet is accessible via one or more network(s) 110. In some examples,the operator device and the user device 112(1)-112(N) may include asubscriber identity module (SIM), such as an eSIM, to identify eachdevice to a telecommunication service provider (also referred to herein,as “telecommunications network”).

FIG. 1B illustrates a detailed view of a telemetry bin within a servicesector of a base station node. The base station node 106 may compriseRRUs 116(1)-116(3) and a baseband unit 126. In the illustrated exampleof FIG. 1A, the base station node 106 is sectorized into three servicesectors, namely sectors 114(1)-114(3). Base station nodes may besectorized, meaning that the 360-degree directional service area isdivided into several service sectors, with each sector being served byan RRU. In some examples, a service sector may be served by more thanone RRU. However, for purposes of clarity and to appropriatelydistinguish between RRUs of different service sectors, this disclosuredescribes each service sector as being served by one RRU.

In the illustrated example, each of three service sectors 114(1)-114(3)are served by dedicated RRUs 116(1)-116(3). Each RRU has a separationdirection of tracking with respect to adjacent RRUs. The RRUs for atri-sector base station node (e.g. base station node with three servicesectors) typically have a 120-degree tracking with respect to the twoadjacent RRUs.

The RRUs 116(1)-116(3) may be configured to receive digital informationand control signals from a baseband unit 126 via cable(s) 128(1)-128(3),and further modulate this information into a radio frequency (RF) signalthat is then transmitted through the RF antenna(s). The RRU 116(1) mayalso receive RF signals from the RF antenna(s), demodulate the RFsignals, and supply the demodulated signals to the baseband unit 126.Each of the RRUs 116(1)-116(3) is connected to the baseband unit 126 viaa dedicated cable. For example, RRU 116(1)(1) is connected to thebaseband unit 126 via cable 128(1), RRU 116(1)(2) via cable 128(2), andRRU 116(1)(3) via cable 128(3). An RRU may be misconfigured if thecables connecting the RRUs 116(1)-116(3) to the baseband unit 126 areswapped. For example, RRU 116(1)(1) may be misconfigured if it isconnected to the baseband unit 126 using cable 128(2) or cable 128(3).

The baseband unit 126 may be configured to process the demodulatedsignals received from the RRUs 116(1)-116(3) into a format suitable fortransmission over a backhaul communication system of atelecommunications network. The baseband unit 126 may also processsignals received from the backhaul communication system and supply theprocessed signals to the RRUs 116(1)-116(3) for modulation into RFsignals.

The RRU configuration controller 102 may capture the telemetry data 104at telemetry bin(s) 120(1)-120(P) that are positioned within the servicesector. In the illustrated example of FIG. 1B, telemetry bin 120(1) maycapture telemetry data 104 associated with user device 112(1)-112(N)that are proximate to the telemetry bin 120(1) within the service sector114(1) (e.g. polygon representation 118(1) of the service sector114(1)).

FIG. 2 illustrates a block diagram for an operation of the RRUconfiguration controller. The RRU configuration controller may capturetelemetry data of a user device that is operating within a servicesector of an RRU. The RF configuration controller is configured tocapture the telemetry data at a telemetry bin 120(1) positioned withinthe service sector.

At 202, a user device 204 may transmit an RF signal to atelecommunications network while the user device 204 is within apredetermined distance of a telemetry bin 206. The user device 204 mayperform similar functions to one of the user device(s) 112(1)-112(P),and the telemetry bin 206 may perform similar functions to one of thetelemetry bin(s) 120(1)-120(P). At the telemetry bin 206, the RFconfiguration controller 102 may detect the presence of the user device204 and pull telemetry data from the user device 112(1)-112(N) that isassociated with the RF transmission. The RRU configuration controller102 may monitor the telemetry bin 206 for telemetry data continuously orper a predetermined schedule, or a triggering event. The predeterminedschedule may be one second, one minute, one hour, or any other suitablyappropriate time interval. The triggering event may correspond todetecting an RF signal transmitted by a user device.

At 208, the RF configuration controller 102 may analyze the telemetrydata 104, in combination with telemetry data captured from other userdevices at the same telemetry bin and other telemetry bins within theservice sector. In doing so, the RF configuration controller 102 maydetermine a signal QoS associated with the serving RRU. The RFconfiguration controller 102 may further analyze the signal QoS todetermine whether the serving RRU is misconfigured. In one embodiment,the RF configuration controller 102 may compare the signal QoS with apredetermined QoS threshold. The predetermined QoS threshold representsa baseline of nominal performance for the serving RRU. A signal QoS lessthan the predetermined QoS threshold reflects an underperformance and alikely misconfigured RRU.

If the RF configuration controller 102 infers that an RRU is likelymisconfigured, the RF configuration controller 102 may generate amessage 122 for delivery to an operator device indicating that an RRUassociated with a base station node is likely misconfigured. The messagemay also indicate that at least one other RRU is likely misconfiguredsince the misconfiguration is premised on a cable swap from a common,baseband unit.

FIG. 3 illustrates various components of an example RRU configurationcontroller. The RRU configuration controller may analyze telemetry dataassociated with RRUs of a base station node and infer whether the RRUsare misconfigured. A misconfigured RRU may describe an RRU that isconnected to a baseband unit using cables intended for another RRU. Thecable swap may cause a marked reduction in RRU performance, ultimatelyimpacting a user device's quality of experience. The RRU configurationcontroller is configured to interface with sectorized base stationnodes, that is, base station nodes that are divided into multipleservice sectors, whereby each service sector is serviced via dedicatedRRUs. By way of example, a tri-sector base station node services three120-degree radial sectors, each of which is served by a dedicated RRU(e.g. three RRUs in total).

The RRU configuration controller 102 may include input/outputinterface(s) 302. The input/output interface(s) 302 may include anysuitable type of output interface known in the art, such as a display(e.g. a liquid crystal display), speakers, a vibrating mechanism, or atactile feedback mechanism. Input/output interface(s) 302 also includesports for one or more peripheral devices, such as headphones, peripheralspeakers, or a peripheral display. Further, the input/outputinterface(s) 302 may further include a camera, a microphone, akeyboard/keypad, or a touch-sensitive display. A keyboard/keypad may bea push-button numerical dialing pad (such as on a typicaltelecommunication device), a multi-key keyboard (such as a conventionalQWERTY keyboard), or one or more other types of keys or buttons, and mayalso include a joystick-like controller and/or designated navigationbuttons, or the like.

Additionally, the RRU configuration controller 102 may include networkinterface(s) 304. The network interface(s) 304 may include any suitablesort of transceiver known in the art. For example, the networkinterface(s) 304 may include a radio transceiver that performs thefunction of transmitting and receiving radio frequency communicationsvia an antenna. Also, the network interface(s) 304 may include awireless communication transceiver and a near-field antenna forcommunicating over unlicensed wireless Internet Protocol (IP) networks,such as local wireless data networks and personal area networks (e.g.Bluetooth or near field communication (NFC) networks). Further, thenetwork interface(s) 304 may include wired communication components,such as an Ethernet port or a Universal Serial Bus (USB). Hardwarecomponent(s) 306 may include additional hardware interface, datacommunication hardware, and data storage hardware.

Further, the RRU configuration controller 102 may include one or moreprocessor(s) 308 that are operably connected to memory 310. In at leastone example, the one or more processor(s) 308 may be a centralprocessing unit(s) (CPU), graphics processing unit(s) (GPU), or both aCPU and GPU or any suitable sort of processing unit(s). Each of the oneor more processor(s) 308 may have numerous arithmetic logic units (ALUs)that perform arithmetic and logical operations as well as one or morecontrol units (CUs) that extract instructions and stored content fromprocessor cache memory, and then execute these instructions by callingon the ALUs, as necessary during program execution. The one or moreprocessor(s) 308 may also be responsible for executing all computerapplications stored in the memory, which can be associated with commontypes of volatile (RAM) and/or non-volatile (ROM) memory.

In some examples, memory 310 may include system memory, which may bevolatile (such as RAM), non-volatile (such as ROM, flash memory, etc.),or some combination of the two. The memory may also include additionaldata storage devices (removable and/or non-removable) such as, forexample, magnetic disks, optical disks, or tape.

The memory 310 may further include non-transitory computer-readablemedia, such as volatile and nonvolatile, removable and non-removablemedia implemented in any suitable method or technology for storage ofinformation, such as computer-readable instructions, data structures,program modules, or other data. System memory, removable storage, andnon-removable storage are all examples of non-transitorycomputer-readable media. Examples of non-transitory computer-readablemedia include, but are not limited to, RAM, ROM, EEPROM, flash memory orother memory technology, CD-ROM, digital versatile disks (DVD) or otheroptical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any suitablenon-transitory medium which can be used to store the desiredinformation.

In the illustrated example, the memory 310 may include an operatingsystem 312, an interface module 314, a telemetry analysis module 316, aninference module 318, a notification module 320, and a data store 322.The operating system 312 may be any suitable operating system capable ofmanaging computer hardware and software resources. The operating system312 may include an interface layer that enables applications tointerface with the input/output interface(s) 302 and the networkinterface(s) 304.

An interface module 314 may be configured to interact with user deviceswithin a service sector of a base station node. The interface module 314may capture telemetry data from user devices based on the location ofthe user devices relative to telemetry bins. The telemetry data may becaptured directly from the user devices, or via a telecommunicationsnetwork. The interface module 314 may be configured to interact withhardware-based telemetry bins (e.g. beacons) that detect the presence ofuser devices within a predetermined distance of the telemetry bins. Oncedetected, the interface module 314 may perform acts to pull thetelemetry data from the user device.

The interface module 314 may also interface with an operator deviceassociated with the base station node, to deliver messages, such as anindication that an RRU is likely misconfigured. The operator device maybe associated with a field worker responsible for the base station node,an operator of the base station node, or any other suitable personnelthat may correct a misconfigured RRU.

The telemetry analysis module 316 may further include a sector overlaycomponent 324, a telemetry bin component 326, a signal QoS datacomponent 328, and a QoS threshold component 330. The sector overlaycomponent 324 may be configured to generate and overlay a polygonrepresentation on a plan-view map of a service sector. The polygonrepresentation may have a vertex at the base station and may overlay thesubstantial QoS bounds of the service sector. The QoS bounds of theservice sector may be based on the geographic area within which theserving RRU can maintain an RF signal with signal QoS data that isgreater than or equal to the predetermined QoS threshold. Accordingly,the profile of the polygon representation may be based on historical QoSvalues of the RRU (e.g. historical QoS values attributable to a properlyconfigured RRU). The sector overlay component 324 may interact with theQoS threshold component 330 to define the bounds of the polygonrepresentation.

While this disclosure describes the use of a polygon representation tobound a geographic area of a service sector, any suitable geometricshape may be adopted that reasonably reflects the QoS bounds of theservice sector.

The telemetry bin component 326 may be configured to pull telemetry datafrom a plurality of telemetry bins located within a service sector.Telemetry bins may be positioned within a polygon representation of aservice sector to capture a representative portion of telemetry datatransmitted within the service sector. The representative portion oftelemetry data may comprise an entirety, near-entirety, or a portionless than an entirety of the telemetry data within the service sector.

A telemetry bin may represent a discrete geographic location within aservice sector of a base station node, from which telemetry data iscaptured. The telemetry bin, itself, may be software-based, such thatthe RRU configuration controller 102, via the interface module 314, maypull telemetry data from user devices that transmit RF signals and movewithin a predetermined proximity of the telemetry bin. The overlay ofthe geolocation of user devices and the discrete geographic location ofa telemetry bin may act as a trigger event to capture telemetry datafrom the user devices. Alternatively, a telemetry bin may behardware-based (e.g. a beacon). A beacon may employ a suitable wirelesscommunication protocol to detect the presence of user devices that movewithin a predetermined proximity of the telemetry bin. Once detected,the RRU configuration controller 102 may pull the telemetry data fromthe user devices. Suitable wireless communication protocols may include2G, 3G, Long-Term Evolution (LTE), 5G-New Radio (5G-NR), Bluetooth®, orWi-Fi®. In this embodiment, the telemetry bin component 326 may interactwith beacons positioned within the service sector.

By way of example, if a user device transmits an RF signal and movesinto a geographic location that is proximate to a telemetry bin, thetelemetry bin component 326 may capture the telemetry data associatedwith the user device (e.g. via a software or a hardware-basedcomponent). Collectively, telemetry bins within a service sector maycapture an entirety, or near-entirety, of telemetry data transmittedwithin the service sector. By extension, the telemetry data captured attelemetry bins within a service sector may be used to quantify theperformance of the serving RRU.

The signal QoS data component 328 may be configured to calculate asignal QoS data for telemetry data captured from telemetry bins within aservice sector. The signal QoS data may describe or measure the overallperformance of an RF signal associated with the RRU, based on thetelemetry data. To measure signal QoS data, the RRU configurationcontroller may analyze a suitable combination of telemetry dataincluding packet loss, bit rate, throughput, latency, availability, andjitter. The signal QoS data may include measurements of a ReferenceSignal Received Power (RSRP) and/or Reference Signal Received Quality(RSRQ), relative to industry QoS standards.

The RSRP is a measurement of the power present in a received radiosignal for telecommunications networks, such as an LTE or 5G-NR network.The RSRP measures the power of LTE reference signals spread over thefull bandwidth and narrow band. An RSRP that is greater than −80 dBm mayindicate excellent signal strength with maximum data throughput rates.In contrast, an RSRP that is less than −110 dBm may indicate no signalstrength. More granular RSRP measurements between −80 dBm and −110 dBmrepresent good, fair, and fair to poor signal strengths.

The RSRQ is a measurement of the quality of the received radio signalfor telecommunications networks, such as an LTE or 5G-NR network. TheRSRQ may provide additional information when RSRP is not sufficient tomake a reliable handover or cell selection decision. An RSRQ that isgreater than −10 dB may indicate excellent signal strength with maximumdata throughput rates. In contrast, an RSRQ that is less than −20 dB mayindicate no signal strength. More granular RSRQ measurements between −10dB and −20 dB represent good, fair, and fair to poor signal strengths.

In a non-limiting example, consider a signal QoS data that is based atleast in part on an RSRP measurement. If the RSRP measurement is greaterthan −80 dBm, this measurement may indicate excellent signal strengthwith maximum data throughput rates. Here, the signal QoS data iscalculated to reflect better than expected performance In contrast, anRSRP that is less than −110 dBm may indicate no signal strength.Accordingly, the signal QoS data is calculated to reflect anunderperformance

The signal QoS data component 328 may calculate the signal QoS data fora service sector by aggregating the telemetry data from telemetry binswithin the service sector and calculate the signal QoS data for theservice sector based on the aggregated telemetry data. In anotherembodiment, signal QoS data component 328 may calculate a signal QoSdata value for each of the telemetry bins within the service sector anddetermine the signal QoS data for the service sector by aggregating thesignal QoS data values of each of the telemetry bins. The latterembodiment may be used by the inference module 318 to identify changesin signal QoS data across the geographic area of the service sector.Changes in signal QoS data may clarify whether an RRU underperformanceis likely due to a misconfiguration or a localized RF signalobstruction.

The signal QoS data component 328 may calculate a QoS score to reflectthe performance of an RRU, based on the signal QoS data of the servicesector. The QoS score may reflect an analysis of the signal QoS datarelative to the QoS threshold. In one embodiment, the QoS score may bebased on the signal QoS data of individual telemetry bins. An aggregateof the QoS scores of each telemetry bin may be used to determine a QoSscore for a service sector. In another embodiment, the QoS score may bebased on an aggregate signal QoS data for the service sector.

The QoS score may be alpha-numeric (i.e. 0 to 10, or A to F),descriptive, (i.e. low, medium, or high), based on color (i.e. green,yellow, red), or any suitable rating scale. A high QoS score (i.e. 7 to10, high, green) may indicate that the RRU is performing better thanexpected. A medium QoS score (e.g. 4 to 6, medium, yellow) may indicatethat the RRU is performing as expected. A low QoS score (e.g. 1 to 3,low, red) may indicate that the RRU is underperforming.

The QoS threshold component 330 may be configured to define a QoSthreshold for each serving RRU of a base station node. The QoS thresholdacts as a service sector baseline of nominal performance that isexpected from an RRU within a service sector. The QoS thresholdcomponent 330 may determine the QoS threshold based on historicaltelemetry data associated with the RRU. For example, the QoS thresholdcomponent 330 may retrieve, from the data store 322, historicaltelemetry data associated with the RRU (e.g. historical QoS valuesattributable to a properly configured RRU). The QoS threshold component330 may employ one or more trained machine-learning algorithms toanalyze the historical telemetry data to determine a QoS threshold. TheQoS threshold may be based on any suitable combination signal QoS data(e.g. downlink throughput, uplink throughput, packet loss, latency,jitter, or echo) or measurements thereof (e.g. RSRP or RSRQ).

The inference module 318 may be configured to analyze signal QoS dataand infer whether an RRU may be misconfigured. The inference module 318may employ one or more machine-learning algorithms to analyze the signalQoS data within a service sector and determine whether the signal QoSdata is indicative of a misconfigured RRU. In one embodiment, analysisof signal QoS data may comprise a comparison of signal QoS data (e.g.signal QoS data component 328) for a service sector relative to apredetermined QoS threshold (e.g. QoS threshold component 330). If thesignal QoS data is less than the predetermined QoS threshold, theinference module 318 may infer that the RRU is likely misconfigured. Ifthe signal QoS data is greater than or equal to the predetermined QoSthreshold, the inference module 318 may infer that the RRU is likelyproperly configured.

In another embodiment, the inference module 318 may analyze the QoSscore associated with the service sector. If the QoS score is low (e.g.1 to 3, low, red), an inference that the RRU is likely misconfigured,may be drawn. If the QoS score is medium (e.g. 4 to 6, medium, yellow)or high (e.g. 7 to 10, high, green), an inference that the RRU is likelyproperly configured, may be drawn.

In yet another embodiment, the inference module 318 may employ one ormore trained machine-learning algorithms to generate a statistical modelthat correlates the discrete geographic positions of telemetry bins withthe historical signal QoS data. The historical signal QoS data mayreflect an expected performance of the RRU across the geographic area ofa service sector. In doing so, the inference module 318 may analyzereal-time, or near-real-time signal QoS data associated with a servicesector relative to data-points of the statistical model to infer whetherthe RRU is misconfigured.

The inference module 318 may also determine whether an underperformingRRU is likely due to a misconfiguration or an RF signal obstruction. Inthis embodiment, the inference module 318 may analyze signal QoS data attelemetry bins within a service sector to determine whetherunderperformance is localized or more generally prevalent across theservice sector. A local underperformance may be attributable to aphysical or electromagnetic RF signal obstruction. Uniformunderperformance within a service sector, or underperformance thatgradually ensues with distance from the base station node, may beindicative of a misconfigured RRU.

In response to inferring that an RRU is likely misconfigured, theinference module 318 may also analyze other RRUs associated with thebase station node. Since a misconfigured RRU is based on an inadvertentcable swap, if one RRU is misconfigured, then at least one other RRUassociated with the base station node is likely misconfigured.

The notification module 320 may generate a message for delivery to anoperator device indicating that an RRU associated with a base stationnode is likely misconfigured. The message may further indicate thelikelihood of misconfiguration based on signal QoS data or a QoS score.Alternatively, the message may indicate that underperformance may beattributed to an RF signal obstruction, based on analysis of signal QoSdata across telemetry bins. The message may also indicate that at leastone other RRU is likely misconfigured since the misconfiguration ispremised on a cable swap from a common, baseband unit.

The data store 322 may include a repository of historical telemetrydata, historical signal QoS data, historical QoS scores, historicalstatistical models, and any suitable data pertinent to an operation ofthe RRU configuration controller 102.

The RRU configuration controller 102, via various modules and componentsmay make use of one or more trained machine-learning algorithms such assupervised learning, unsupervised learning, semi-supervised learning,naive Bayes, Bayesian network, decision trees, neural networks, fuzzylogic models, and/or probabilistic classification models.

FIGS. 4 and 5 present processes 400 and 500 that relate to operations ofthe RF configuration controller 102. Each of processes 400 and 500illustrate a collection of blocks in a logical flow chart, whichrepresents a sequence of operations that can be implemented in hardware,software, or a combination thereof. In the context of software, theblocks represent computer-executable instructions that, when executed byone or more processors, perform the recited operations. Generally,computer-executable instructions may include routines, programs,objects, components, data structures, and the like that performparticular functions or implement particular abstract data types. Theorder in which the operations are described is not intended to beconstrued as a limitation, and any number of the described blocks can becombined in any order and/or in parallel to implement the process. Fordiscussion purposes, the processes 400 and 500 are described withreference to the computing environment 100 of FIG. 1.

FIG. 4 illustrates an exemplary process for capturing telemetry datawithin a service sector of an RRU and determining whether the RRU ismisconfigured, in accordance with at least one embodiment. Amisconfigured RRU may refer to an RRU that is connected to a basebandunit using a cable intended for another RRU. The inadvertent cable swapmay cause the RRU to experience a marked reduction in performance,ultimately impacting a subscriber's quality of experience. Process 400is described from the perspective of the RRU configuration controller.

At 402, the RRU configuration controller may capture telemetry data fromuser devices within a service sector of a base station. The RRUconfiguration controller may capture the telemetry data from a series oftelemetry bins positioned throughout the service sector. The telemetrydata be associated with RF signals transmitted by user devices while theuser devices are proximate to a telemetry bin. The telemetry data mayinclude downlink throughput, uplink throughput, packet loss, latency,jitter, echo, or any suitable combination thereof.

At 404, the RRU configuration controller may analyze the telemetry datato determine a signal QoS data associated with the service sector. Thesignal QoS data may describe or measure the overall performance of an RFsignal associated with the RRU, based on the telemetry data, and asexperienced by the user device. The signal QoS data may be based onsuitable combinations of telemetry data and may also includemeasurements of a Reference Signal Received Power (RSRP) and/orReference Signal Received Quality (RSRQ).

At 406, the RF configuration controller may compare the signal QoS datawith an expected performance measure of the RRU to determine whether theRRU is likely misconfigured or performing as expected. In oneembodiment, the RF configuration controller may compare the signal QoSdata with a predetermined QoS threshold. The predetermined QoS thresholdmay be based on historical telemetry data and reflect the expectedperformance of the RRU. Signal QoS data that is less than thepredetermined QoS threshold may reflect an underperforming RRU,indicative of a misconfiguration. Signal QoS data that is greater thanor equal to the predetermined QoS threshold may reflect an expected, orbetter than expected, performance of the RRU.

In another embodiment, the RF configuration controller may generate astatistical model based on historical signal QoS data. The historicalsignal QoS data may reflect the expected performance of the serving RRUwithin the service sector. In doing so, signal QoS data may be analyzedrelative to data-points of the statistical model to infer whether theRRU is misconfigured.

If the RF configuration controller determines that the RRU is properlyconfigured, process 400 may return to process step 402 and continue tocapture telemetry data from user devices within the service sector.Rather than ending process 400, the RF configuration controller maycontinuously capture telemetry data from the service sector, to lessenany time interval that a change in configuration at the RRU, or anotherRRU operating at the same base station node, may have on the quality ofservice within the service sector. If the RF configuration controllerdetermines that the RRU is misconfigured, the process 400 may proceed toblock 408.

At 408, the RF configuration controller may generate a message thatindicates that the RRU is likely misconfigured. The message may alsoindicate that another RRU on the base station node is likelymisconfigured since the misconfiguration is premised on a cable swapbetween RRUs.

The RF configuration controller may deliver the message to an operatordevice associated with the base station node. The operator device may beassociated with a field worker responsible for the base station node, anoperator of the base station node, or any other suitable personnel thatmay correct a misconfigured RRU.

FIG. 5 illustrates an exemplary process for determining whether an RRUis misconfigured or subject to a localized RF signal obstruction, inaccordance with at least one embodiment. Process 500 is premised on theRRU configuration controller analyzing calculating signal QoS datarelative to telemetry bins within a service sector. Since telemetry binsare positioned within a service sector at different geolocations,calculating signal QoS data relative to telemetry bins can providevisibility to changes in signal QoS data across the geographic area ofthe service sector. Process 500 is described from the perspective of theRRU configuration controller.

At 502, the RF configuration controller may capture telemetry data at aplurality of telemetry bins within a service sector of a base stationnode. The telemetry data may be associated with user devices thattransmit RF signals (e.g. inbound or outboard RF transmissions) within apredetermined distance of a telemetry bin.

At 504, the RF configuration controller may analyze the telemetry datato determine a signal QoS data associated with each telemetry bin. Indoing so, the RF configuration controller may generate a profile ofsignal QoS data across the geographic area of the service sector.

At 506, the RF configuration controller may analyze the profile ofsignal QoS data across the service sector to determine whether signalQoS data is uniform across the services sector, whether changes insignal QoS data are uniform within the service sector relative to thedistance from the base station node, or whether changes in signal QoSdata are localized to segment(s) of the service sector.

If the RF configuration controller determines that the signal QoS datais uniform or there is a uniform rate of change of signal QoS datarelative to the distance from the base station node, the process 500 mayproceed to block 508. Uniform signal QoS data may indicate that thesignal QoS data is not impacted by an RF signal obstruction. A uniformrate of change of signal QoS data relative to a base station node mayreflect an expected signal attenuation that is typical of RF signals. Auniform rate of signal attenuation with distance from the RRU canreflect a properly configured RRU. Accordingly, at 508, the RFconfiguration controller may infer that any underperformance of the RRU,as determined by process 400, is likely due to a misconfigured RRU.

Otherwise, if the RF configuration controller determines that the signalQoS data or the rate of change of signal QoS data relative to thedistance from the base station node is non-uniform, the process 500 mayproceed to block 510. At 510, the RF configuration controller maydetermine that changes in signal QoS data are localized to thesegment(s) of the service sector. Here, the localized change in signalQoS data is such that it does not reflect an expected signal attenuationof RF signals. Accordingly, the RF configuration controller may inferthat an RF signal obstruction likely impacts the service sector.

CONCLUSION

Although the subject matter has been described in language specific tofeatures and methodological acts, it is to be understood that thesubject matter defined in the appended claims is not necessarily limitedto the specific features or acts described herein. Rather, the specificfeatures and acts are disclosed as exemplary forms of implementing theclaims.

What is claimed:
 1. A system, comprising: one or more processors; memorycoupled to the one or more processors, the memory including one or moremodules that are executable by the one or more processors to: capturetelemetry data within a service sector of a base station node; determinea signal Quality of Service (QoS) associated with the service sector,based at least in part on the telemetry data; and infer whether a RemoteRadio Unit (RRU) associated with the service sector is misconfigured,based at least in part on the signal QoS data.
 2. The system of claim 1,wherein the telemetry data includes at least one of signal strength,signal interference, data throughput, or data latency.
 3. The system ofclaim 1, wherein the one or more modules are further executable by theone or more processors to: determine an QoS threshold associated withthe service sector, based at least in part on the RRU of the servicesector, and wherein, to infer that the RRU is misconfigured is based atleast in part on a comparison of the signal QoS data and the QoSthreshold.
 4. The system of claim 3, wherein the one or more modules arefurther executable by the one or more processors to: retrieve, from adata store, historical telemetry data associated with the RRU, andwherein, to determine the QoS threshold for the RRU is based at least inpart on the historical telemetry data.
 5. The system of claim 1, whereinthe one or more modules are further executable by the one or moreprocessors to: identify discrete geographic positions within the servicesector as telemetry bins, the telemetry bins to capture individualinstances of the telemetry data, and wherein, to determine a signal QoSdata is based at least in part on analysis of the telemetry datacaptured at the telemetry bins.
 6. The system of claim 1, wherein theone or more modules are further executable by the one or more processorsto: generate a polygon representation to overlay a map of a geographicregion serviced by the RRU, the polygon representation having a vertexat the base station node, and wherein capturing telemetry within theservice sector further comprises capturing telemetry data within anenclosure that is bound by the polygon representation.
 7. The system ofclaim 1, wherein the one or more modules are further executable by theone or more processors to: assign a QoS score to the telemetry data,based at least in part on the signal QoS data, and wherein to infer thatthe RRU is misconfigured is based at least in part on the QoS scorebeing less than a predetermined QoS threshold.
 8. The system of claim 1,wherein, the RRU corresponds to a first RRU and the service sectorcorresponds to a first service sector, wherein, the base station nodecomprises at least the first RRU that services the first service sectorand a second RRU that serves a second sector, wherein, the first RRU iscommunicatively connected to a baseband unit via a first cable and thesecond RRU is communicatively connected to the baseband unit via asecond cable, and wherein, to infer that the RRU misconfiguredcorresponds to inferring that the first RRU is connected to the basebandunit via the second cable.
 9. The system of claim 1, wherein the one ormore modules are further executable by the one or more processors to:generate a message for delivery to a user device associated with thebase station node, the message indicating that the RRU associated withthe service sector is likely misconfigured.
 10. A computer-implementedmethod, comprising: under control of one or more processors: capturing,from individual telemetry bins within a service sector of a base stationnode, telemetry data associated with signal performance of an RRU of thebase station node; determining a signal QoS data for the individualtelemetry bins, based at least in part on the telemetry data; andinferring whether the RRU associated with the service sector ismisconfigured, based at least in part on the signal QoS data for theindividual telemetry bins.
 11. The computer-implemented method of claim10, further comprising: determining an QoS threshold value for theservice sector, based at least in part on historical QoS data associatedwith the RRU, and wherein, inferring whether the RRU is misconfigured isbased at least in part on the QoS threshold value.
 12. Thecomputer-implemented method of claim 10, further comprising: retrieving,from a data-store, historical signal QoS data associated with theindividual telemetry bins; generating a statistical model thatcorrelates signal QoS data with discrete geographic positions within theservice sector, based at least in part on the historical signal QoSdata; and analyzing the signal QoS data for the individual telemetrybins with data-points of the statistical model, and wherein, inferringwhether the RRU is misconfigured is based at least in part on acorrelation of the signal QoS data with the data-points of thestatistical model.
 13. The computer-implemented method of claim 10,further comprising: generating a polygon representation to overlay a mapof a geographic region serviced by the RRU, a profile of the polygonrepresentation being based on historical QoS values that are greaterthan or equal to an QoS threshold value of the service sector; andidentifying the individual telemetry bins within the service sector,based on geographic coordinates of the individual telemetry binsoccurring in an enclosure created by the polygon representation.
 14. Thecomputer-implemented method of claim 10, further comprising: assigning aQoS score to the individual telemetry bins within the service sector,based at least in part on the signal QoS data; and generating a servicesector QoS score by aggregating the QoS score of the individualtelemetry bins, and wherein to infer that the RRU is misconfigured isbased at least in part on the service sector QoS score being less than apredetermined QoS threshold.
 15. The computer-implemented method ofclaim 10, wherein the RRU corresponds to a first RRU, and wherein thebase station node comprises the first RRU, a second RRU and a third RRU,and further comprising: in response to inferring that the first RRU ismisconfigured, determining a second signal QoS data for a second set oftelemetry bins associated with the second RRU and a third signal QoSdata for a third set of telemetry bins associated with the third RRU;and identifying at least one of the second RRU or the third RRU as beingmisconfigured, based at least in part on the second signal QoS data andthe third signal QoS data.
 16. The computer-implemented method of claim10, further comprising: in response to determining that the RRU ismisconfigured, generating a message for delivery to a user deviceassociated with base station node, the message indicating that the RRUassociated with the service sector is likely misconfigured.
 17. Anon-transitory computer-readable media storing computer-executableinstructions that, when executed on one or more processors, collectivelycause computers to perform acts comprising: capturing, from individualtelemetry bins within a service sector of a base station node, telemetrydata associated with signal performance of an RRU of the base stationnode; determining a signal QoS data for the individual telemetry binswithin the service sectors; generating a service sector QoS byaggregating the signal QoS data for the individual telemetry bins; andinferring whether the RRU associated with the service sector ismisconfigured, based at least in part on the service sector QoS.
 18. Thenon-transitory computer-readable media of claim 17, wherein the signalQoS data includes at least one of signal strength, signal interference,data throughput, or data latency.
 19. The non-transitorycomputer-readable media of claim 17, wherein acts further comprise:determining an QoS threshold value for the service sector, based atleast in part on historical QoS data associated with the RRU, andwherein, inferring whether the RRU is misconfigured is based at least inpart on a comparison of the service sector QoS and the QoS thresholdvalue.
 20. The non-transitory computer-readable media of claim 17,wherein the RRU corresponds to a first RRU, and wherein the base stationnode includes the first RRU and a second RRU, and wherein, inferringthat the RRU is misconfigured corresponds to an inference that the RRUis communicatively coupled to a baseband unit via a cable associatedwith the second RRU.